Pandas Profiling Report

Dataset statistics

Number of variables	13
Number of observations	2891
Missing cells	48
Missing cells (%)	0.1%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	293.7 KiB
Average record size in memory	104.0 B

Variable types

Categorical	4
Numeric	8
DateTime	1

Alerts

`updated_at` has constant value "2022-12-10 21:24:34.727669"	Constant
`city` has a high cardinality: 567 distinct values	High cardinality
`male_population` is highly overall correlated with `female_population` and 4 other fields	High correlation
`female_population` is highly overall correlated with `male_population` and 4 other fields	High correlation
`total_population` is highly overall correlated with `male_population` and 4 other fields	High correlation
`number_of_veterans` is highly overall correlated with `state` and 6 other fields	High correlation
`foreign_born` is highly overall correlated with `male_population` and 4 other fields	High correlation
`state` is highly overall correlated with `median_age` and 3 other fields	High correlation
`state_code` is highly overall correlated with `state` and 3 other fields	High correlation
`count` is highly overall correlated with `male_population` and 4 other fields	High correlation
`median_age` is highly overall correlated with `state` and 1 other fields	High correlation
`average_household_size` is highly overall correlated with `state` and 1 other fields	High correlation
`city` is uniformly distributed	Uniform

Reproduction

Analysis started	2022-12-10 13:30:55.321834
Analysis finished	2022-12-10 13:31:14.967163
Duration	19.65 seconds
Software version	pandas-profiling vv3.5.0
Download configuration	config.json

city
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	567
Distinct (%)	19.6%
Missing	0
Missing (%)	0.0%
Memory size	22.7 KiB

Bloomington	15
Columbia	15
Springfield	15
Jackson	10
Norwalk	10
Other values (562)	2826

Length

Max length	47
Median length	25
Mean length	9.1030785
Min length	2

Characters and Unicode

Total characters	26317
Distinct characters	56
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	0.1%

Sample

1st row	Silver Spring
2nd row	Quincy
3rd row	Hoover
4th row	Rancho Cucamonga
5th row	Newark

Common Values

Value	Count	Frequency (%)
Bloomington	15	0.5%
Columbia	15	0.5%
Springfield	15	0.5%
Jackson	10	0.3%
Norwalk	10	0.3%
Lakewood	10	0.3%
Arlington	10	0.3%
Fayetteville	10	0.3%
Rochester	10	0.3%
Albany	10	0.3%
Other values (557)	2776	96.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
city	98	2.5%
san	72	1.9%
beach	51	1.3%
valley	40	1.0%
saint	40	1.0%
santa	40	1.0%
new	34	0.9%
fort	29	0.8%
park	25	0.7%
hills	24	0.6%
Other values (598)	3392	88.2%

Most occurring characters

Value	Count	Frequency (%)
a	2515	9.6%
e	2366	9.0%
n	2076	7.9%
o	2007	7.6%
r	1595	6.1%
i	1579	6.0%
l	1569	6.0%
t	1297	4.9%
s	1045	4.0%
	959	3.6%
Other values (46)	9309	35.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	21452	81.5%
Uppercase Letter	3853	14.6%
Space Separator	959	3.6%
Dash Punctuation	28	0.1%
Other Punctuation	25	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	2515	11.7%
e	2366	11.0%
n	2076	9.7%
o	2007	9.4%
r	1595	7.4%
i	1579	7.4%
l	1569	7.3%
t	1297	6.0%
s	1045	4.9%
d	697	3.2%
Other values (18)	4706	21.9%

Uppercase Letter

Value	Count	Frequency (%)
C	475	12.3%
S	405	10.5%
B	293	7.6%
P	248	6.4%
L	243	6.3%
M	237	6.2%
R	229	5.9%
A	227	5.9%
F	170	4.4%
W	157	4.1%
Other values (14)	1169	30.3%

Other Punctuation

Value	Count	Frequency (%)
'	20	80.0%
/	5	20.0%

Space Separator

Value	Count	Frequency (%)
	959	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	28	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	25305	96.2%
Common	1012	3.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	2515	9.9%
e	2366	9.3%
n	2076	8.2%
o	2007	7.9%
r	1595	6.3%
i	1579	6.2%
l	1569	6.2%
t	1297	5.1%
s	1045	4.1%
d	697	2.8%
Other values (42)	8559	33.8%

Common

Value	Count	Frequency (%)
	959	94.8%
-	28	2.8%
'	20	2.0%
/	5	0.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	26314	> 99.9%
None	3	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	2515	9.6%
e	2366	9.0%
n	2076	7.9%
o	2007	7.6%
r	1595	6.1%
i	1579	6.0%
l	1569	6.0%
t	1297	4.9%
s	1045	4.0%
	959	3.6%
Other values (44)	9306	35.4%

None

Value	Count	Frequency (%)
ü	2	66.7%
ó	1	33.3%

state
Categorical

Distinct	49
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	22.7 KiB

California	676
Texas	273
Florida	222
Illinois	91
Washington	85
Other values (44)	1544

Length

Max length	20
Median length	13
Mean length	8.4268419
Min length	4

Characters and Unicode

Total characters	24362
Distinct characters	46
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Maryland
2nd row	Massachusetts
3rd row	Alabama
4th row	California
5th row	New Jersey

Common Values

Value	Count	Frequency (%)
California	676	23.4%
Texas	273	9.4%
Florida	222	7.7%
Illinois	91	3.1%
Washington	85	2.9%
Arizona	80	2.8%
Colorado	80	2.8%
Michigan	79	2.7%
North Carolina	70	2.4%
Virginia	70	2.4%
Other values (39)	1165	40.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
california	676	21.2%
texas	273	8.6%
florida	222	7.0%
new	141	4.4%
carolina	94	2.9%
illinois	91	2.9%
washington	85	2.7%
arizona	80	2.5%
colorado	80	2.5%
north	80	2.5%
Other values (44)	1366	42.8%

Most occurring characters

Value	Count	Frequency (%)
a	3650	15.0%
i	3033	12.4%
o	2207	9.1%
n	2073	8.5%
r	1675	6.9%
l	1435	5.9%
s	1390	5.7%
e	1136	4.7%
C	894	3.7%
f	681	2.8%
Other values (36)	6188	25.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	20882	85.7%
Uppercase Letter	3183	13.1%
Space Separator	297	1.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	3650	17.5%
i	3033	14.5%
o	2207	10.6%
n	2073	9.9%
r	1675	8.0%
l	1435	6.9%
s	1390	6.7%
e	1136	5.4%
f	681	3.3%
t	580	2.8%
Other values (14)	3022	14.5%

Uppercase Letter

Value	Count	Frequency (%)
C	894	28.1%
M	341	10.7%
T	317	10.0%
N	276	8.7%
F	222	7.0%
I	210	6.6%
A	148	4.6%
W	130	4.1%
O	119	3.7%
V	70	2.2%
Other values (11)	456	14.3%

Space Separator

Value	Count	Frequency (%)
	297	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	24065	98.8%
Common	297	1.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	3650	15.2%
i	3033	12.6%
o	2207	9.2%
n	2073	8.6%
r	1675	7.0%
l	1435	6.0%
s	1390	5.8%
e	1136	4.7%
C	894	3.7%
f	681	2.8%
Other values (35)	5891	24.5%

Common

Value	Count	Frequency (%)
	297	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24362	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	3650	15.0%
i	3033	12.4%
o	2207	9.1%
n	2073	8.5%
r	1675	6.9%
l	1435	5.9%
s	1390	5.7%
e	1136	4.7%
C	894	3.7%
f	681	2.8%
Other values (36)	6188	25.4%

median_age
Real number (ℝ)

Distinct	180
Distinct (%)	6.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	35.494881

Minimum	22.9
Maximum	70.5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	22.7 KiB

Quantile statistics

Minimum	22.9
5-th percentile	28.8
Q1	32.8
median	35.3
Q3	38
95-th percentile	42.6
Maximum	70.5
Range	47.6
Interquartile range (IQR)	5.2

Descriptive statistics

Standard deviation	4.4016167
Coefficient of variation (CV)	0.12400709
Kurtosis	4.164544
Mean	35.494881
Median Absolute Deviation (MAD)	2.6
Skewness	0.64661844
Sum	102615.7
Variance	19.37423
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
35.7	50	1.7%
33.4	48	1.7%
33.1	45	1.6%
36.8	45	1.6%
34.1	45	1.6%
34.5	44	1.5%
38.1	42	1.5%
34.6	40	1.4%
35.3	40	1.4%
36	40	1.4%
Other values (170)	2452	84.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
22.9	5	0.2%
23	4	0.1%
23.5	5	0.2%
23.6	5	0.2%
23.9	5	0.2%
24.2	5	0.2%
25.5	5	0.2%
26	5	0.2%
26.1	5	0.2%
26.2	10	0.3%

Value	Count	Frequency (%)
70.5	3	0.1%
48.8	5	0.2%
47.9	4	0.1%
47.6	4	0.1%
47.4	5	0.2%
47.3	5	0.2%
47	5	0.2%
46.9	5	0.2%
46.8	4	0.1%
45.9	4	0.1%

male_population
Real number (ℝ)

Distinct	593
Distinct (%)	20.5%
Missing	3
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%
Mean	97328.426

Minimum	29281
Maximum	4081698
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	22.7 KiB

Quantile statistics

Minimum	29281
5-th percentile	32290
Q1	39289
median	52341
Q3	86641.75
95-th percentile	296902.6
Maximum	4081698
Range	4052417
Interquartile range (IQR)	47352.75

Descriptive statistics

Standard deviation	216299.94
Coefficient of variation (CV)	2.2223717
Kurtosis	209.81379
Mean	97328.426
Median Absolute Deviation (MAD)	15991
Skewness	12.735597
Sum	2.810845 × 10⁸
Variance	4.6785663 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
40601	10	0.3%
33993	10	0.3%
135455	5	0.2%
518317	5	0.2%
149547	5	0.2%
60989	5	0.2%
60704	5	0.2%
83640	5	0.2%
55550	5	0.2%
42100	5	0.2%
Other values (583)	2828	97.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
29281	5	0.2%
29995	5	0.2%
30007	5	0.2%
30193	4	0.1%
30758	5	0.2%
30799	2	0.1%
30844	5	0.2%
30890	5	0.2%
31019	5	0.2%
31205	5	0.2%

Value	Count	Frequency (%)
4081698	5	0.2%
1958998	5	0.2%
1320015	5	0.2%
1149686	5	0.2%
786833	5	0.2%
741270	5	0.2%
721405	5	0.2%
693826	5	0.2%
639019	5	0.2%
518317	5	0.2%

female_population
Real number (ℝ)

Distinct	594
Distinct (%)	20.6%
Missing	3
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%
Mean	101769.63

Minimum	27348
Maximum	4468707
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	22.7 KiB

Quantile statistics

Minimum	27348
5-th percentile	34163
Q1	41227
median	53809
Q3	89604
95-th percentile	315853.35
Maximum	4468707
Range	4441359
Interquartile range (IQR)	48377

Descriptive statistics

Standard deviation	231564.57
Coefficient of variation (CV)	2.2753799
Kurtosis	227.63305
Mean	101769.63
Median Absolute Deviation (MAD)	15771
Skewness	13.320445
Sum	2.9391069 × 10⁸
Variance	5.3622151 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
35801	10	0.3%
41862	5	0.2%
57422	5	0.2%
508602	5	0.2%
151293	5	0.2%
61247	5	0.2%
65417	5	0.2%
92957	5	0.2%
144323	5	0.2%
43511	5	0.2%
Other values (584)	2833	98.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
27348	5	0.2%
31238	4	0.1%
31456	4	0.1%
32173	3	0.1%
32397	5	0.2%
32745	5	0.2%
32763	4	0.1%
32799	5	0.2%
32807	5	0.2%
32901	5	0.2%

Value	Count	Frequency (%)
4468707	5	0.2%
2012898	5	0.2%
1400541	5	0.2%
1148942	5	0.2%
826172	5	0.2%
776168	5	0.2%
748419	5	0.2%
701081	5	0.2%
661063	5	0.2%
508602	5	0.2%

total_population
Real number (ℝ)

Distinct	594
Distinct (%)	20.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	198966.78

Minimum	63215
Maximum	8550405
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	22.7 KiB

Quantile statistics

Minimum	63215
5-th percentile	67271
Q1	80429
median	106782
Q3	175232
95-th percentile	618619
Maximum	8550405
Range	8487190
Interquartile range (IQR)	94803

Descriptive statistics

Standard deviation	447555.93
Coefficient of variation (CV)	2.2494003
Kurtosis	219.21588
Mean	198966.78
Median Absolute Deviation (MAD)	32640
Skewness	13.044623
Sum	5.7521296 × 10⁸
Variance	2.0030631 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
68097	10	0.3%
71024	10	0.3%
82463	5	0.2%
104808	5	0.2%
87873	5	0.2%
73432	5	0.2%
248956	5	0.2%
66872	5	0.2%
107899	5	0.2%
451949	5	0.2%
Other values (584)	2831	97.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
63215	5	0.2%
63651	5	0.2%
63792	5	0.2%
64609	5	0.2%
64819	4	0.1%
64837	5	0.2%
64962	5	0.2%
65052	4	0.1%
65058	5	0.2%
65065	5	0.2%

Value	Count	Frequency (%)
8550405	5	0.2%
3971896	5	0.2%
2720556	5	0.2%
2298628	5	0.2%
1567442	5	0.2%
1563001	5	0.2%
1469824	5	0.2%
1394907	5	0.2%
1300082	5	0.2%
1026919	5	0.2%

number_of_veterans
Real number (ℝ)

Distinct	577
Distinct (%)	20.0%
Missing	13
Missing (%)	0.4%
Infinite	0
Infinite (%)	0.0%
Mean	9367.8325

Minimum	416
Maximum	156961
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	22.7 KiB

Quantile statistics

Minimum	416
5-th percentile	1990
Q1	3739
median	5397
Q3	9368
95-th percentile	29511
Maximum	156961
Range	156545
Interquartile range (IQR)	5629

Descriptive statistics

Standard deviation	13211.22
Coefficient of variation (CV)	1.410275
Kurtosis	39.853818
Mean	9367.8325
Median Absolute Deviation (MAD)	2281
Skewness	5.2959233
Sum	26960622
Variance	1.7453633 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4211	10	0.3%
5714	10	0.3%
5204	10	0.3%
3397	10	0.3%
3116	10	0.3%
3647	10	0.3%
3063	10	0.3%
5532	10	0.3%
3404	9	0.3%
3027	9	0.3%
Other values (567)	2780	96.2%
(Missing)	13	0.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
416	3	0.1%
629	5	0.2%
693	4	0.1%
705	5	0.2%
724	5	0.2%
776	4	0.1%
780	5	0.2%
897	5	0.2%
1066	4	0.1%
1101	5	0.2%

Value	Count	Frequency (%)
156961	5	0.2%
109089	5	0.2%
92489	5	0.2%
85417	5	0.2%
75432	5	0.2%
72388	5	0.2%
72042	5	0.2%
71898	5	0.2%
61995	5	0.2%
54995	5	0.2%

foreign_born
Real number (ℝ)

Distinct	587
Distinct (%)	20.4%
Missing	13
Missing (%)	0.4%
Infinite	0
Infinite (%)	0.0%
Mean	40653.599

Minimum	861
Maximum	3212500
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	22.7 KiB

Quantile statistics

Minimum	861
5-th percentile	3215
Q1	9224
median	18822
Q3	33971.75
95-th percentile	109222.15
Maximum	3212500
Range	3211639
Interquartile range (IQR)	24747.75

Descriptive statistics

Standard deviation	155749.1
Coefficient of variation (CV)	3.8311271
Kurtosis	310.38784
Mean	40653.599
Median Absolute Deviation (MAD)	11101
Skewness	16.355795
Sum	1.1700106 × 10⁸
Variance	2.4257783 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
5757	10	0.3%
13409	10	0.3%
30908	5	0.2%
56514	5	0.2%
21959	5	0.2%
8948	5	0.2%
10599	5	0.2%
24503	5	0.2%
9257	5	0.2%
6630	5	0.2%
Other values (577)	2818	97.5%
(Missing)	13	0.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
861	5	0.2%
1058	5	0.2%
1062	4	0.1%
1224	5	0.2%
1531	5	0.2%
1699	5	0.2%
1789	5	0.2%
1815	5	0.2%
1884	5	0.2%
2064	5	0.2%

Value	Count	Frequency (%)
3212500	5	0.2%
1485425	5	0.2%
696210	5	0.2%
573463	5	0.2%
401493	5	0.2%
373842	5	0.2%
326825	5	0.2%
300702	5	0.2%
297199	5	0.2%
260789	5	0.2%

average_household_size
Real number (ℝ)

Distinct	161
Distinct (%)	5.6%
Missing	16
Missing (%)	0.6%
Infinite	0
Infinite (%)	0.0%
Mean	2.7425426

Minimum	2
Maximum	4.98
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	22.7 KiB

Quantile statistics

Minimum	2
5-th percentile	2.22
Q1	2.43
median	2.65
Q3	2.95
95-th percentile	3.58
Maximum	4.98
Range	2.98
Interquartile range (IQR)	0.52

Descriptive statistics

Standard deviation	0.43329109
Coefficient of variation (CV)	0.15798883
Kurtosis	2.8619082
Mean	2.7425426
Median Absolute Deviation (MAD)	0.24
Skewness	1.4095639
Sum	7884.81
Variance	0.18774117
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2.4	78	2.7%
2.72	68	2.4%
2.97	55	1.9%
2.39	54	1.9%
2.64	54	1.9%
2.41	50	1.7%
2.68	50	1.7%
2.52	49	1.7%
2.73	48	1.7%
2.55	45	1.6%
Other values (151)	2324	80.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2	5	0.2%
2.06	5	0.2%
2.08	10	0.3%
2.1	4	0.1%
2.11	5	0.2%
2.12	5	0.2%
2.13	15	0.5%
2.15	10	0.3%
2.16	9	0.3%
2.17	10	0.3%

Value	Count	Frequency (%)
4.98	5	0.2%
4.78	4	0.1%
4.58	5	0.2%
4.57	3	0.1%
4.43	4	0.1%
4.15	5	0.2%
4.13	5	0.2%
4.08	10	0.3%
3.97	5	0.2%
3.93	5	0.2%

state_code
Categorical

Distinct	49
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	22.7 KiB

CA	676
TX	273
FL	222
IL	91
WA	85
Other values (44)	1544

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	5782
Distinct characters	24
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	MD
2nd row	MA
3rd row	AL
4th row	CA
5th row	NJ

Common Values

Value	Count	Frequency (%)
CA	676	23.4%
TX	273	9.4%
FL	222	7.7%
IL	91	3.1%
WA	85	2.9%
AZ	80	2.8%
CO	80	2.8%
MI	79	2.7%
NC	70	2.4%
VA	70	2.4%
Other values (39)	1165	40.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
ca	676	23.4%
tx	273	9.4%
fl	222	7.7%
il	91	3.1%
wa	85	2.9%
az	80	2.8%
co	80	2.8%
mi	79	2.7%
nc	70	2.4%
va	70	2.4%
Other values (39)	1165	40.3%

Most occurring characters

Value	Count	Frequency (%)
A	1210	20.9%
C	894	15.5%
N	425	7.4%
T	414	7.2%
L	387	6.7%
M	341	5.9%
I	339	5.9%
X	273	4.7%
O	244	4.2%
F	222	3.8%
Other values (14)	1033	17.9%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	5782	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	1210	20.9%
C	894	15.5%
N	425	7.4%
T	414	7.2%
L	387	6.7%
M	341	5.9%
I	339	5.9%
X	273	4.7%
O	244	4.2%
F	222	3.8%
Other values (14)	1033	17.9%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5782	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	1210	20.9%
C	894	15.5%
N	425	7.4%
T	414	7.2%
L	387	6.7%
M	341	5.9%
I	339	5.9%
X	273	4.7%
O	244	4.2%
F	222	3.8%
Other values (14)	1033	17.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5782	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	1210	20.9%
C	894	15.5%
N	425	7.4%
T	414	7.2%
L	387	6.7%
M	341	5.9%
I	339	5.9%
X	273	4.7%
O	244	4.2%
F	222	3.8%
Other values (14)	1033	17.9%

race
Categorical

Distinct	5
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	22.7 KiB

Hispanic or Latino	596
White	589
Black or African-American	584
Asian	583
American Indian and Alaska Native	539

Length

Max length	33
Median length	25
Mean length	16.940505
Min length	5

Characters and Unicode

Total characters	48975
Distinct characters	26
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Hispanic or Latino
2nd row	White
3rd row	Asian
4th row	Black or African-American
5th row	White

Common Values

Value	Count	Frequency (%)
Hispanic or Latino	596	20.6%
White	589	20.4%
Black or African-American	584	20.2%
Asian	583	20.2%
American Indian and Alaska Native	539	18.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
or	1180	15.9%
hispanic	596	8.0%
latino	596	8.0%
white	589	8.0%
black	584	7.9%
african-american	584	7.9%
asian	583	7.9%
american	539	7.3%
indian	539	7.3%
and	539	7.3%
Other values (2)	1078	14.6%

Most occurring characters

Value	Count	Frequency (%)
a	6761	13.8%
i	5745	11.7%
n	5099	10.4%
	4516	9.2%
r	2887	5.9%
c	2887	5.9%
A	2829	5.8%
e	2251	4.6%
o	1776	3.6%
t	1724	3.5%
Other values (16)	12500	25.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	37603	76.8%
Uppercase Letter	6272	12.8%
Space Separator	4516	9.2%
Dash Punctuation	584	1.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	6761	18.0%
i	5745	15.3%
n	5099	13.6%
r	2887	7.7%
c	2887	7.7%
e	2251	6.0%
o	1776	4.7%
t	1724	4.6%
s	1718	4.6%
l	1123	3.0%
Other values (7)	5632	15.0%

Uppercase Letter

Value	Count	Frequency (%)
A	2829	45.1%
L	596	9.5%
H	596	9.5%
W	589	9.4%
B	584	9.3%
I	539	8.6%
N	539	8.6%

Space Separator

Value	Count	Frequency (%)
	4516	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	584	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	43875	89.6%
Common	5100	10.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	6761	15.4%
i	5745	13.1%
n	5099	11.6%
r	2887	6.6%
c	2887	6.6%
A	2829	6.4%
e	2251	5.1%
o	1776	4.0%
t	1724	3.9%
s	1718	3.9%
Other values (14)	10198	23.2%

Common

Value	Count	Frequency (%)
	4516	88.5%
-	584	11.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	48975	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	6761	13.8%
i	5745	11.7%
n	5099	10.4%
	4516	9.2%
r	2887	5.9%
c	2887	5.9%
A	2829	5.8%
e	2251	4.6%
o	1776	3.6%
t	1724	3.5%
Other values (16)	12500	25.5%

count
Real number (ℝ)

Distinct	2785
Distinct (%)	96.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	48963.774

Minimum	98
Maximum	3835726
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	22.7 KiB

Quantile statistics

Minimum	98
5-th percentile	778.5
Q1	3435
median	13780
Q3	54447
95-th percentile	162670.5
Maximum	3835726
Range	3835628
Interquartile range (IQR)	51012

Descriptive statistics

Standard deviation	144385.59
Coefficient of variation (CV)	2.9488247
Kurtosis	246.57282
Mean	48963.774
Median Absolute Deviation (MAD)	12231
Skewness	12.973526
Sum	1.4155427 × 10⁸
Variance	2.0847198 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
535	3	0.1%
713	3	0.1%
1343	3	0.1%
876	3	0.1%
6547	3	0.1%
1615	3	0.1%
251	3	0.1%
881	3	0.1%
1713	2	0.1%
906	2	0.1%
Other values (2775)	2863	99.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
98	1	< 0.1%
128	1	< 0.1%
158	1	< 0.1%
182	1	< 0.1%
203	1	< 0.1%
204	1	< 0.1%
211	1	< 0.1%
216	1	< 0.1%
219	1	< 0.1%
227	1	< 0.1%

Value	Count	Frequency (%)
3835726	1	< 0.1%
2485125	1	< 0.1%
2192248	1	< 0.1%
2177650	1	< 0.1%
1936732	1	< 0.1%
1386389	1	< 0.1%
1374535	1	< 0.1%
1304564	1	< 0.1%
1240092	1	< 0.1%
1161455	1	< 0.1%

updated_at
Date

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	22.7 KiB

Minimum	2022-12-10 21:24:34.727669
Maximum	2022-12-10 21:24:34.727669

Histogram

Histogram with fixed size bins (bins=1)

Auto

The auto setting is an interpretable pairwise column metric of the following mapping:

Variable_type-Variable_type : Method, Range
Categorical-Categorical : Cramer's V, [0,1]
Numerical-Categorical : Cramer's V, [0,1] (using a discretized numerical column)
Numerical-Numerical : Spearman's ρ, [-1,1]

The number of bins used in the discretization for the Numerical-Categorical column pair can be changed using config.correlations["auto"].n_bins. The number of bins affects the granularity of the association you wish to measure.

This configuration uses the recommended metric for each pair of columns.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

First rows
Last rows

	city	state	median_age	male_population	female_population	total_population	number_of_veterans	foreign_born	average_household_size	state_code	race	count	updated_at
0	Silver Spring	Maryland	33.8	40601.0	41862.0	82463	1562.0	30908.0	2.60	MD	Hispanic or Latino	25924	2022-12-10 21:24:34.727669
1	Quincy	Massachusetts	41.0	44129.0	49500.0	93629	4147.0	32935.0	2.39	MA	White	58723	2022-12-10 21:24:34.727669
2	Hoover	Alabama	38.5	38040.0	46799.0	84839	4819.0	8229.0	2.58	AL	Asian	4759	2022-12-10 21:24:34.727669
3	Rancho Cucamonga	California	34.5	88127.0	87105.0	175232	5821.0	33878.0	3.18	CA	Black or African-American	24437	2022-12-10 21:24:34.727669
4	Newark	New Jersey	34.6	138040.0	143873.0	281913	5829.0	86253.0	2.73	NJ	White	76402	2022-12-10 21:24:34.727669
5	Peoria	Illinois	33.1	56229.0	62432.0	118661	6634.0	7517.0	2.40	IL	American Indian and Alaska Native	1343	2022-12-10 21:24:34.727669
6	Avondale	Arizona	29.1	38712.0	41971.0	80683	4815.0	8355.0	3.18	AZ	Black or African-American	11592	2022-12-10 21:24:34.727669
7	West Covina	California	39.8	51629.0	56860.0	108489	3800.0	37038.0	3.56	CA	Asian	32716	2022-12-10 21:24:34.727669
8	O'Fallon	Missouri	36.0	41762.0	43270.0	85032	5783.0	3269.0	2.77	MO	Hispanic or Latino	2583	2022-12-10 21:24:34.727669
9	High Point	North Carolina	35.5	51751.0	58077.0	109828	5204.0	16315.0	2.65	NC	Asian	11060	2022-12-10 21:24:34.727669

	city	state	median_age	male_population	female_population	total_population	number_of_veterans	foreign_born	average_household_size	state_code	race	count	updated_at
2881	Gulfport	Mississippi	35.1	33108.0	38764.0	71872	6646.0	3072.0	2.54	MS	White	42870	2022-12-10 21:24:34.727669
2882	Davis	California	26.3	33493.0	34163.0	67656	2176.0	13997.0	2.69	CA	American Indian and Alaska Native	779	2022-12-10 21:24:34.727669
2883	Los Angeles	California	35.0	1958998.0	2012898.0	3971896	85417.0	1485425.0	2.86	CA	Black or African-American	404868	2022-12-10 21:24:34.727669
2884	Mount Vernon	New York	38.5	31876.0	36745.0	68621	2064.0	23777.0	2.85	NY	Hispanic or Latino	9446	2022-12-10 21:24:34.727669
2885	Lynchburg	Virginia	28.7	38614.0	41198.0	79812	4322.0	4364.0	2.48	VA	White	53727	2022-12-10 21:24:34.727669
2886	Stockton	California	32.5	150976.0	154674.0	305650	12822.0	79583.0	3.16	CA	American Indian and Alaska Native	19834	2022-12-10 21:24:34.727669
2887	Southfield	Michigan	41.6	31369.0	41808.0	73177	4035.0	4011.0	2.27	MI	American Indian and Alaska Native	983	2022-12-10 21:24:34.727669
2888	Indianapolis	Indiana	34.1	410615.0	437808.0	848423	42186.0	72456.0	2.53	IN	White	553665	2022-12-10 21:24:34.727669
2889	Somerville	Massachusetts	31.0	41028.0	39306.0	80334	2103.0	22292.0	2.43	MA	American Indian and Alaska Native	374	2022-12-10 21:24:34.727669
2890	Coral Springs	Florida	37.2	63316.0	66186.0	129502	4724.0	38552.0	3.17	FL	White	90896	2022-12-10 21:24:34.727669

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Other Punctuation

Space Separator

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

None

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Interactions

Correlations

Auto

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Phik (φk)

Missing values

Sample